I ONLY NEED THE ANSWER FOR #2.

1. The decision tree (hierarchy) below was constructed to help decide which, among several types of computers, should be purchased. The weights were decided upon by the prospective buyer who was looking for a new computer. Note that all the criteria are objective and can easily be quantified except reliability which has been rated by an expert on a scale from 1 to 10 , with 1 being very reliable and 10 being very unreliable. The following table gives the ratings of each altemative computer with reapect to the above criteria. a. Compute the weights associated with each means objective (bottom row of hierarchy) b. Determine the single dimension value functions (SDVF) for each means objective. Assume all SDVF are linear functions. c. Combine the four SDVFs into a multi-objective function (use additive value function). d. Compute the value for each alternative using your multi-objective function. ONLY NEED THE ANSWER TO \#2! 2. When the computer buyer looked at the actual weights used to make the decision, he decided that the hierarchy should not be used and that swing weights should be used instead. He gave the following parameters: - Processor Speed and RAM are of equal importance - Reliability is twice as important as RAM - Price is 1.5 times more important than Reliability a. Compute the swing weights associated with each means objective b. Combine the four SDVFs (from =1b ) into a multi-objective function (use additive value function) with the new swing weights. c. Compute the value for each alternative using your multi-objective function. d. . Using both sets of your results, i. What alternative do you recommend and why? ii. What is your second choice and why? iii. Do the results from both methods result in the same recommendation/decision